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Theory

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Papers

Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums Optimization NIPS 2017
Early stopping for kernel boosting algorithms: A general analysis with localized complexities NIPS 2017
On the Optimization Landscape of Tensor Decompositions NIPS 2017
On the Complexity of Learning Neural Networks NIPS 2017
Improving Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms and Its Applications NIPS 2017
Convergence Analysis of Two-layer Neural Networks with ReLU Activation NIPS 2017
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching NIPS 2017
Spectrally-normalized margin bounds for neural networks NIPS 2017
Optimal Sample Complexity of M-wise Data for Top-K Ranking NIPS 2017
The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings NIPS 2017
Minimizing a Submodular Function from Samples NIPS 2017
A graph-theoretic approach to multitasking NIPS 2017
Fitting Low-Rank Tensors in Constant Time NIPS 2017
Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search NIPS 2017
Tensor Biclustering NIPS 2017
Estimating Mutual Information for Discrete-Continuous Mixtures NIPS 2017
On the Consistency of Quick Shift NIPS 2017
Evaluation Metrics for Machine Reading Comprehension: Prerequisite Skills and Readability ACL 2017
Argument Mining with Structured SVMs and RNNs ACL 2017
On the Flatness of Loss Surface for Two-layered ReLU Networks ACML 2017
Conditions beyond treewidth for tightness of higher-order LP relaxations AISTATS 2017
Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation AISTATS 2017
The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits AISTATS 2017
A Lower Bound on the Partition Function of Attractive Graphical Models in the Continuous Case AISTATS 2017
Diverse Neural Network Learns True Target Functions AISTATS 2017